Malnutrition of hospitalized patients can adversely affect clinical outcomes and cost. Several nutritional screening tools have been developed to identify patients with malnutrition risk. However, many of those possess practical pitfalls of requiring much time and labor to administer and may not be highly applicable to a Korean population. This study sought to develop and evaluate a Nutrition Risk Screening Tool (NRST) which is simple and quick to administer and widely applicable to Korean hospitalized patients with various diseases. The study was also designed to generate a screening tool predictable of various clinical outcomes and to validate it against the Nutritional Risk Screening 2002 (NRS 2002). Electronic medical records of 424 patients hospitalized at a general hospital in Seoul during a 14-month period were abstracted for anthropometric, medical, biochemical, and clinical outcome variables. The study employed a 4-step process consisting of selecting NRST components, searching a scoring scheme, validating against a reference tool, and confirming clinical outcome predictability. NRST components were selected by stepwise multiple regression analysis of each clinical outcome (i.e., hospitalization period, complication, disease progress, and death) on several readily available patient characteristics. Age and serum levels of albumin, hematocrit (Hct), and total lymphocyte count (TLC) remained in the last model for any of 4 dependent variables were decided as NRST components. Odds ratios of malnutrition risk based on NRS 2002 according to levels of the selected components were utilized to frame a scoring scheme of NRST. A NRST score higher than 3.5 was set as a cut-off score for malnutrition risk based on sensitivity and specificity levels against NRS 2002. Lastly differences in clinical outcomes by patients' NRST results were examined. The results showed that the NRST can significantly predict the in-hospital clinical outcomes. It is concluded that the NRST can be useful to simply and quickly screen patients at high-nutritional risk in relation to prospective clinical outcomes.
The Doam watershed is located at alpine areas and the annual average precipitation, including snow accumulation, is significant higher than other areas. Thus, pollutant laden runoff and sediment discharge from the alpine agricultural fields are causing water quality degradation at the Doam watershed. To estimate soil erosion from the agricultural fields, the Universal Soil Loss Equation (USLE) has been widely used because of its simplicity to use. In the early spring at the Doam watershed, the stream flow increases because of snow melt, which results in erosion of loosened soil experiencing freezing and thaw during the winter. Also, extremely torrential rainfall, such as the typhoons 'RUSA' in 2002 and 'MAEMI' in 2003, caused significant amounts of soil erosion and sediment at the Doam watershed. However, the USLE model cannot simulate impacts on soil erosion of freezing and thaw of the soil. It cannot estimate sediment yield from a single torrential rainfall event. Also, it cannot simulate temporal changes in USLE input parameters. Thus, the Soil and Water Assessment Tool (SWAT) model was investigated for its applicability to estimate soil erosion at the Doam watershed, instead of the widely used USLE model. The SWAT hydrology and erosion/sediment components were validated after calibration of the hydrologic component. The R$^2$ and Nash-Sutcliffe coefficient values are higher enough, thus it is found the SWAT model can be efficiently used to simulate hydrology and sediment yield at the Doam watershed. The effects of snow melt on SWAT estimated stream flow and sediment were investigated using long-term precipitation and temperature data at the Doam watershed. It was found significant amount of flow and sediment in the spring are contributed by melting snow accumulated during the winter. Two typhoons in 2002 and 2003, MAEMI and RUSA, caused 33% and 22% of total sediment yields at the Doam watershed, respectively. Thus, it is recommended that the SWAT model, capable of simulating snow melt, sediment yield from a single storm event, and long-term weather data, needs to be used in estimating soil erosion at alpine agricultural areas to develop successful soil erosion management instead of the USLE.
There has been continuous efforts to manage the water resources for the required water quality criterion at river channel in Korea. However, we could not obtain the partial improvement only for the point source pollutant such as, wastewater from urban and industrial site through the water quality management. Therefore, it is strongly needed that the Best Management Practice(BMP) throughout the river basin for water quality management including non-point source pollutant loads. This problem should be resolved by recognizing the non-point source pollutant loads from upstream river basin to the outlet depends on the land use and soil type characteristic of the river basin using the computer simulation by distributed parameter model based on the detailed investigation and the application of Geographic Information System(GIS). Used in this study, Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) model is a tool suitable for long term evaluation of the effects of BMPs and can be used for un gauged watershed simulation of runoff and sediment yield. Now applications of model are in progress. So we just describe the limited result. However If well have done modeling and have investigated of propriety of model, well achieve our final goal of this study.
Hyun, Shinwoo;Seo, Bo Hun;Lee, Sukin;Kim, Kwang Soo
Korean Journal of Agricultural and Forest Meteorology
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v.22
no.3
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pp.194-204
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2020
Cultivar parameters, which are key inputs to a crop growth model, have been estimated using observation data in good quality. Observation data with high quality often require considerable labor and cost, which makes it challenging to gather a large quantity of data for calibration of cultivar parameters. Alternatively, data in sufficient quantity can be collected from the reports on the evaluation of cultivars by region although these data are of questionable quality. The objective of our study was to assess the quality of crop and management data available from the reports on the regional adaptation trials for rice cultivars. We also aimed to propose the measures for improvement of the data quality, which would aid reliable estimation of cultivar parameters. DatasetRanker, which is the tool designed for quantitative assessment of the data for parameter calibration, was used to evaluate the quality of the data available from the regional adaptation trials. It was found that these data for rice cultivars were classified into the Silver class, which could be used for validation or calibration of key cultivar parameters. However, those regional adaptation trial data would fall short of the quality for model improvement. Additional information on management, e.g., harvest and irrigation management, can increase the quantitative quality by 10% with the minimum effort and cost. The quality of the data can also be improved through measurements of initial conditions for crop growth simulations such as soil moisture and nutrients. In addition, crop model improvement can be facilitated using crop growth data in time series, which merits further studies on development of approaches for non-destructive methods to monitor the crop growth.
This study is to identify the efficiency in Busan social welfare agencies between input factors and output factors. For this purpose, gathered are the 2001 services reports of those study agencies. This study used 4 difference model, model 1; comparing input factor(social worker number & labor cost) about output factor(the total number of program used person), model 2; comparing input factor(the total number of social welfare agencies staff & the total working expenses) about output factor(the total number of program used person), model 3; comparing input factor(the total number of volunteer, social welfare agencies staff & a period of operation) about output factor(the total number of program used person), model 4; comparing input factor(the total number of volunteer, social welfare agencies staff, a period of operation & the total working expenses) about output factor(the total number of program used person). Charnes's study(1978) provided an analytical tool for efficiency services output of non-profit organizations, and DEA(Data Envelopment Analysis) was a analytical framework for evaluating the impact of social service outcome. the finding are as follows : (1) In the results of comparing 4 models as same standard, we can find 35-55%(16-25) efficiency agencies among the 45 social welfare agencies. (2) For all DMU becoming the efficiency 1 to standard of output factor, model 1; 33 agencies are increasing the social worker number($\Delta$0.8 number), 10 agencies are raising the labor cost of social worker($\Delta$1,189,000 Won), model 2; 30 agencies are increasing the total number of social welfare agencies staff($\Delta$1.25 number), 14 agencies are raising the total working expenses($\Delta$1,447,000 Won), model 3; 8 agencies are increasing the total number of social welfare agencies staff($\Delta$2.26 number), 14 agencies are increasing the total number of volunteer($\Delta$52 number), and 10 agencies are increasing a period of operation($\Delta$13 month), model 4; 24 agencies are increasing the total number of social welfare agencies staff($\Delta$1.8 number), 12 agencies are raising the total working expenses($\Delta$5,017,000 Won), 12 agencies are increasing the total number of volunteer($\Delta$43.2 number), and 23 agencies are increasing a period of operation($\Delta$16 month).
Journal of the Korea Academia-Industrial cooperation Society
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v.17
no.6
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pp.418-428
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2016
The participants in an urban and housing redevelopment project were categorized as construction companies, government employees, and housing cooperatives. This study analyzed how a public management system affects the continuous participation intention using comprehensive project satisfaction. The specific factors for the evaluation items of a public management system were composed using advanced research. A hypothesis and research model was set up and verified using the PLS-SEM model to analyse how the continuous participation intention is affected by the public management system via comprehensive projects satisfaction. Setting the project plan and selecting the project tool, as well as post management and sustainability affect the comprehensive projects satisfaction meaningfully in the case of construction companies. The participation of the user, and post management and sustainability affect the comprehensive project satisfaction meaningfully in the case of government employees. The operating organization and using and participation of the user affect the comprehensive project satisfaction meaningfully in the case of a housing cooperative. The comprehensive project satisfaction affects the continuity of the participation meaningfully in the case of all of project participants.
Journal of the Korean Society of Marine Environment & Safety
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v.22
no.6
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pp.647-653
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2016
There are no ex-port evaluations for the propriety and efficiency of AtoNs considering risk elements and environmental changes after the opening of a port. It is necessary to develop objective indicators and evaluation models to fill this gap. This study establishes an efficiency analysis model for Aids to Navigation (ANEffic) focusing on manned lighthouse, which include 20 function indices. After running a function assessment, an Analytic Hierarchy Process (AHP) and Likert scale are used to address port operations, national policies and expert opinions. As the result of the assessment, Yeongdo, Gageodo, Geomundo and Jukbyun Lighthouses are highly regarded in the propriety and efficiency of AtoN. And Uleungdo, Gasado, Songdaemal and Ulgi Lighthouses need to review detailed evaluations. The ANEffic developed should be utilized as basic tool to collect data for efficient management and to re-arrange the policy decisions regarding AtoNs as appropriate.
Journal of the Korean Society of Hazard Mitigation
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v.8
no.6
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pp.137-148
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2008
There have been many cases of using wetlands as an alternative in controlling stormwater, treating mining leachate, and agricultural discharge, and so on, recently. The reality is, however, that the wetlands are not properly applicable because of the lack of enough longterm data for wetlands due to the difficulty of long-term monitoring. Therefore, this study tries to analyze the storage of Upo, Mokpo, Sajipo, and Jjokjibeul in Topyeong watershed using SWAT(Soil and Water Assessment Tool) model, one of the long-term runoff hydrologic model, for the purpose of generating the long-term data and analyzing the hydrologic behavior of wetlands based on the generated data. Also, the changes in runoff at the outlet are analyzed after applying the simulation of constructing washland in Topyeong watershed and the storage in Upo is analyzed. The result shows that the runoff at the outlet of the watershed is decreased in rainy season from July to August and increased in dry season from December to February. In addition, the analysis of Upo storage concludes that Upo can be influenced by the construction of the washland. The duration curve of washland is then analyzed in order to evaluate the wetland's sustainability in terms of washland and it appears that the runoff of washland is simulated to be less than that of the existing wetland. Moreover, runoffs of some washlands are simulated to be less even in wet season. These results lead to the fact that there should be further hydrologic management for constructed washland. Then, the changes in loads (TN and TP) because of constructing washland are analyzed. The result shows that the loads are reduced because of the construction. Also, the changes in loads due to the construction of buffer strips are analyzed to compare the load reductions caused by a washland. Finally, REMM model, a riparian management model, is applied to overcome the hydrologic ambiguousness of SWAT model, and then, the SWAT model results are compared to those of REMM.
Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.
Journal of the Korean Association of Geographic Information Studies
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v.19
no.3
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pp.1-15
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2016
The study of ecosystem service assessment has been actively researched and developed from Millennium Ecosystem Assessment(MA) and The Economics of Ecosystems and Biodiversity(TEEB). However, current assessments are limited to monetary assessments of ecosystem function and do not account for the effects of environmental factors and socioeconomic status. This study proposes methods to evaluate ecosystem service based on environmental and socioeconomic factors. The study assesses water yield function through the water yield model in InVEST Tool, and evaluates the overall ecosystem service of water yield as reflected by the amount of precipitation and population of the area. Results show that a difference exists between spatial distributions of the ecosystem function of water yield derived from natural conditions such as land cover and soil, and the spatial distribution of the ecosystem service that accounts for climate and socioeconomic factors. The value of ecosystem service increases for an area of higher population and lower precipitation with similar water yield. Thus, the ecosystem service of water yield should be evaluated not only by the water yield function, but also by climate and socioeconomic factors. The evaluation process described for this study should also be applicable to the evaluation of ecological services in other sectors.
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